Search Results (517)

Modern transportation systems impose stringent requirements on high-speed railway (HSR) communications in terms of high data rate and high reliability. Conventional radio frequency (RF) links are limited by the scarcity of spectrum resources, whereas free-space optical (FSO) links are highly vulnerable to atmospheric turbulence and weather conditions. To overcome the limitations of a single transmission medium, this paper proposes and investigates a hybrid FSO/RF selection combining (SC) communication system for narrow-strip cells in HSR scenarios. First, a geometric coverage model is established for heterogeneous base-station deployment, together with a location-aware activation mechanism that enables adaptive activation of base stations according to train positions. Then, by taking practical railway operating conditions into account, the FSO link is modeled to capture the combined effects of atmospheric turbulence, pointing errors, and atmospheric attenuation, while the RF link is modeled as a composite channel incorporating path loss, shadow fading and small-scale fading. Based on this framework, exact closed-form expressions for the system edge coverage probability (ECP) and the percentage of cell coverage area (CCA) are derived. For the sake of comparisons, theoretical expressions of the standalone FSO and standalone RF links are also obtained. Finally, Monte-Carlo simulations are conducted to verify the validity of the derived analytical results. The numerical comparisons demonstrate excellent agreement between the analytical predictions and simulation results, with average relative deviations of only 0.047% for ECP and 0.095% for the percentage of CCA. Compared with either the standalone FSO system or standalone RF system, the proposed hybrid architecture achieves superior coverage performance across different transmit powers, weather conditions, and cell diameters, offering a highly reliable and robust networking solution for future seamless broadband HSR communication systems. Full article

Colorectal cancer progression and therapeutic response are determined not only by tumor-intrinsic programs but also by neural, stromal, and immune components of the tumor microenvironment. However, biologically interpretable transcriptomic scores that jointly capture neural/stromal remodeling and immune activation remain limited. We developed a neuro-immune score (NIS), defined as the neural/stromal module score minus the immune activation module score. NIS was constructed using the combined TCGA-COAD/READ colorectal cancer cohort and externally evaluated in independent Gene Expression Omnibus (GEO) datasets. Single-cell RNA sequencing, focused ligand–receptor analysis, and spatial transcriptomics were further integrated to characterize the cellular origins, spatial organization, and potential mechanisms underlying NIS-associated biology. A high NIS (NIS-high) was associated with adverse prognosis in bulk transcriptomic cohorts. External validation demonstrated that a high NIS was significantly associated with worse disease-free survival/relapse-free survival (DFS/RFS) in GSE39582 and worse overall survival in GSE17536. A multi-cohort meta-analysis further supported a consistent association between NIS-high and poor clinical outcomes. Single-cell analysis localized the NIS-high signal mainly to glial-like cells, fibroblasts, pericytes, endothelial cells, and malignant epithelial cells, whereas CD8+ T cells and natural killer cells exhibited low NIS. Focused ligand–receptor analysis suggested that NIS-high cellular compartments may communicate with immune and tumor compartments through MIF-CD74/CXCR4, SPP1-CD44, extracellular matrix (ECM)–integrin, TGF-β, and immune checkpoint-related axes. Spatial transcriptomics further demonstrated that NIS-high regions were enriched in stromal, neural/glial-like, vascular/pericyte, and tumor–stromal niches, whereas NIS-low regions were associated with immune-activated and cytotoxic T/NK cell-rich areas. NIS captures a spatially organized state of the colorectal cancer microenvironment characterized by neural/stromal remodeling, activation of ECM and vascular/pericyte niches, and relatively reduced or spatially segregated immune activation. NIS may serve as a biologically interpretable microenvironment stratification score associated with adverse outcomes. It also provides a framework for future studies targeting stromal remodeling, myeloid-mediated immune regulation, neural-associated signaling, and antitumor immunity. Full article

High renewable energy penetration and surging electrical demand challenge the operation of integrated electricity–gas systems (IEGS) due to source and load uncertainties. This paper proposes a multi-objective optimal scheduling framework that harnesses flexible resources within the IEGS to balance economic, environmental, and energy efficiency goals. First, a liquid storage tank is introduced to reform the traditional carbon capture, utilization, and storage system. Additionally, a hydrogen energy multi-utilization structure—integrating two-stage power-to-gas, hydrogen fuel cells, and hydrogen storage—is developed to improve operational flexibility under renewable fluctuations and carbon constraints. Second, electric vehicles (EVs) schedulability is quantitatively evaluated across different charging scenarios, defining carbon quotas and profit calculation methods to incentivize EV participation. To address source-load uncertainties, a two-stage robust optimization model utilizing a box uncertainty set and budget constraints is constructed to secure the optimal scheduling solution under worst-case scenarios. Finally, by introducing penalty factors for carbon emissions and energy loss, the multi-objective function is transformed into a single-objective problem to minimize operation costs, emissions, and energy wastage. The results show that the coupled CCUS–HEMU configuration reduces the total and environmental costs by 15.50% and 77.13%. Under the worst-case source–load scenario, bidirectional EV charging further reduces the total cost by 22.10%, increases renewable-energy utilization from 87.34% to 94.34%, and decreases load fluctuation and the maximum peak–valley difference by 68.95% and 14.85%, respectively, thereby enhancing the system’s low-carbon flexibility and robustness against operational uncertainties. Full article

Feature selection is critical for resolving cell-type heterogeneity in single-cell RNA sequencing (scRNA-seq). DUBStepR (Determining the Underlying Basis using Stepwise Regression) is a widely used gene selection method for scRNA-seq designed to identify feature genes that maximize cell-type separation. DUBStepR has been reported to perform effectively in this domain; however, its reliance on linear Pearson correlation and rigid thresholding limits its effectiveness on complex, high-dimensional datasets. Three enhancements are presented in this study: RFCell-DUBStepR, which uses random forests to capture expression-level importance; Copula-DUBStepR, which models non-linear correlations via Gaussian Copulas; and Zqt-DUBStepR, which utilizes quantile-based selection for improved gene retention. Using both simulated and real-world datasets (scRNA-seq), these modifications are shown to resolve the biases of the original algorithm. The modified methods consistently select a more representative gene set and yield higher clustering accuracy across varying levels of biological complexity. These findings establish the modified DUBStepR frameworks as more reliable tools for high-fidelity subpopulation identification in downstream single-cell analysis. Full article

Breast cancer remains one of the most common malignancies worldwide. Highly invasive HER2-positive breast cancer carries a high risk of metastasis and poses a significant therapeutic challenge. Boron neutron capture therapy (BNCT) may be an option for patients with this severe diagnosis. Here we evaluated the effectiveness of BNCT with elemental boron nanoparticles obtained by laser fragmentation and coated Silane-PEG-COOH and conjugated with the Affibody _ZHER2:342 guide protein (BPs) against the HER2-positive breast cancer. The MTT assay after BNCT with BPs revealed an almost twofold reduction in surviving BT-474 tumor cells compared to the control group. The results of the clonogenic test showed totally death of BT-474 cells after BNCT with BPs at a concentration of 40 μg/mL in the culture medium. The same results was found for in vivo. In female SCID mice bearing BT-474 breast tumor xenografts, BNCT with intratumoral injection of BPs at a dose of 60 mg/kg led to a significant slowdown in xenograft growth beginning on the 17th day compared with control animals and the 39th day compared with irradiated females. A single intratumoral administration of BPs at a dose of 60 mg/kg did not show toxic effects. Histological examinations did not reveal systemic accumulation of the studied BPs in major organs; instead BPs was selectively retained within the xenografts and surrounding tissues. Thus, laser fragmented functionalized with Silane-PEG-COOH and the Affibody _ZHER2:342 (BPs B-PEG-AFF) represent a promising platform for boron delivery in targeted BNCT applications. Full article

Average daily gain (ADG) is a core quantitative trait determining the economic benefits of Ashidan yak, a polled new breed adapted to cold barn feeding on the Qinghai–Tibet Plateau. Unraveling its complex genetic architecture is crucial for early molecular breeding selection. In this study, high-depth whole-genome resequencing (WGS) data from 474 Ashidan yaks were used to conduct combined evaluation of genome-wide association study (GWAS) and genomic selection (GS). During GWAS analysis, sex and measurement batch were included as fixed effects, while birth weight and principal components (PC1–PC3) were incorporated as covariates. Multi-model association analysis using GLM, MLM, and FarmCPU was performed on 3.36 million LD-pruned SNPs. The genomic inflation factors (λ ≈ 1.0) for MLM and FarmCPU confirmed effective elimination of population stratification. A total of 11 genome-wide significant SNP loci and 7 key candidate genes including PDE10A, RAD51B, BCAS3 and KCNH8 were identified via the FarmCPU model. Functional enrichment analysis indicated that these gene clusters are significantly involved in cAMP signaling pathway, regulation of ion channel activity, as well as extracellular matrix remodeling of blood vessels and skeletal muscle cells. For genomic selection, a single-trait GBLUP model was constructed using 22.87 million high-density raw SNPs to fully capture polygenic minor effects. Moderately high narrow-sense genomic heritability of ADG was estimated at h² = 0.3233 (p < 0.05). The average independent prediction accuracy across the 10-fold cross-validation reached an average of R = 0.14 ± 0.07. To evaluate marker prioritized genomic evaluation without data leakage, a strict 10-fold cross-validation scheme was implemented, where the top 1% high-priority variant set (~228,000 SNPs) was screened independently within each training fold. The resulting unbiased prediction accuracy reached R = 0.1328 ± 0.1566 (with an average RMSE of 0.3793 ± 0.0066 and a regression slope of 0.4183 ± 0.5055). Comparing this with the unselected whole-genome baseline (R = 0.14 ± 0.07) indicates that naive marker selection based solely on GBLUP effect size in small reference cohorts is influenced by sampling variance, highlighting the need to integrate multi-omics functional annotations for future custom breeding array development. This study provides quantitative insights into the polygenic architecture of ADG in yaks, offering baseline data for genomic selection and custom array development for indigenous livestock on the Qinghai–Tibet Plateau. Full article

We present a microfluidic platform for real-time, label-free cytometry and sorting of single cells based on intrinsic biophysical properties. The system integrates impedance-based electrokinetic sensing with a constriction microchannel architecture to induce controlled deformation during cell transit. Electrical signals captured via lock-in amplification are processed through a parallel software pipeline incorporating deep learning algorithms for event detection and feature extraction. A biomechanical model enables conversion of raw signal features into cell size and whole-cell elasticity, validated against imaging measurements. Experimental results demonstrate accurate phenotyping and sorting of live and dead MCF-7 cells, achieving sorting accuracy of 84%. This approach offers a cost-effective and scalable solution for biophysical analysis, with potential applications in liquid biopsy, disease diagnostics, and personalized medicine. Full article

Persistent HIV-1 reservoirs remain a major barrier to a durable functional cure despite long-term suppressive antiretroviral therapy. Although resting memory CD4⁺ T cells constitute the best-characterized cellular reservoir, tissue microenvironments shape viral persistence and immune clearance. The rectal mucosa represents a specialized tissue niche containing HIV-susceptible target cells, antigen-presenting cells, microbial products, inflammatory cues, and local metabolic signals. Within this setting, myeloid-lineage cells, particularly tissue-resident macrophages and dendritic cells, may contribute to HIV-1 persistence through mechanisms distinct from classical T-cell latency. Here, we review how rectal mucosal macrophages may support HIV-1 persistence through longevity, resistance to apoptosis, metabolic adaptation, epigenetic regulation, and sequestration of virions within virus-containing compartments. We also discuss the dual role of mucosal dendritic cells as sentinels that capture and transfer HIV-1 to CD4⁺ T cells, while considering the limited evidence for inducible proviral persistence in selected anatomical and cellular contexts. Importantly, we further distinguish bona fide reservoir-bearing cells from reservoir-supportive mechanisms, including viral capture, trans-infection, immune suppression, and niche-mediated protection. We also highlight how mucosal dysbiosis, barrier disruption, microbial metabolites, chronic interferon signaling, and immunoregulatory myeloid programs may stabilize HIV-1 persistence in rectal tissues. Integrating intact proviral assays, functional measurements, single-cell profiling, multiplex imaging, and spatial transcriptomics will be critical for defining myeloid-associated persistence and guiding tissue-targeted HIV-1 cure strategies. Full article

Accurate state-of-health estimation of lithium-ion batteries under high-temperature conditions (40–50 °C) remains challenging because of accelerated electrochemical degradation and strongly nonlinear aging patterns. This paper presents a hybrid Ridge regression–convolutional bidirectional long short-term memory framework with a dual-level transfer learning strategy. A Ridge regression baseline first captures the global degradation trend, after which a convolutional bidirectional long short-term memory network learns the nonlinear residuals. For cross-battery adaptation, Ridge coefficients are transferred through prior-regularized regression, and the pre-trained network is fine-tuned using limited target-domain data. The method is validated on cycling datasets from three institutions, namely Tsinghua University, the University of Oxford, and Tongji University, covering 15 batteries under temperatures up to 50 °C. Four health-related features are extracted and adaptively denoised using locally weighted scatterplot smoothing. In single-battery extrapolation, the proposed method achieves a root mean square error as low as 0.0009 on cell B6 at 50 °C, outperforming random forest, long short-term memory, bidirectional long short-term memory, and Ridge regression by 91.1%, 88.6%, 87.7%, and 82.0%, respectively. A cross-battery ablation experiment showed that the dual-level transfer learning strategy reduced the root mean square error from approximately 0.009 to 0.0028, whereas increasing network complexity alone yielded only marginal improvement. A further hierarchical ablation showed that jointly adapting the Ridge prior and the residual network achieved a mean RMSE of 0.004325, representing reductions of 9.39%, 4.14%, and 6.92% relative to the no-adaptation, Ridge-only adaptation, and residual-network-only adaptation configurations, respectively. Full article

This study presents a first-principles dynamic model for the electrochemical production of lithium hydroxide (LiOH) in a bench-scale cation exchange membrane (CEM) cell. Its distinguishing feature is a single, dynamically coupled description of the whole cell, in which the lumped Ordinary Differential Equation (ODE) dynamics of the anodic and cathodic chambers are coupled to a spatially resolved Nernst–Planck (PDE) model of membrane ion transport. The model resolves the transient induction period of ion crossover and captures the association kinetics of Li⁺ and ${\mathrm{OH}}^{-}$, cathodic water reduction, and the back-migration and neutralization of ${\mathrm{OH}}^{-}$ at the anode, with the local electric field represented by a non-linear potential gradient. Solved by the Method of Lines and reduced through symbolic treatment of the Robin boundary conditions to a consistent ODE system, it yields a numerically robust framework for this stiff, strongly coupled problem. Two process-level results emerge: the membrane strongly attenuates cross-chamber disturbances, largely decoupling the anode and cathode, and it reaches a quasi-steady state far faster than the bulk chambers—a separation of time scales expected to widen at larger volume-to-surface-area ratios. These insights inform scale-up strategies and multiscale control architectures for the cell. Full article

The primary aim of this review is to summarize current evidence from clinical and pre-clinical studies on endogenous molecular biomarkers associated with radiosensitivity and radioresistance in cervical cancer, including patients treated with photon-based radiotherapy, cervical cancer cell lines, and xenograft models, and to evaluate the association of these biomarkers with radiotherapy response, residual disease, recurrence and survival, and experimental measures of radiosensitivity. A systematic literature review was conducted for studies published over the last 10 years that evaluated associations between genomic, epigenetic, or protein biomarkers and radiotherapy response or survival outcomes in cervical cancer. Eligible studies included in the current analysis summarize clinical, translational, and pre-clinical studies in correlation with photon-based radiotherapy. Research focusing exclusively on non-coding RNAs, exogenous radiosensitizers, or non-photon modalities was excluded. In total, 112 studies were identified, and 46 of them met the inclusion criteria. The identified biomarkers clustered into several key biological processes: DNA damage response and cell cycle regulation, cancer stemness, hypoxia and microenvironment, epigenetic and transcriptional regulation, and signaling pathways, including exosome-mediated communication. Most markers were linked to radioresistance and adverse outcomes, whereas a smaller subset was associated with increased radiosensitivity. A limited group of biomarkers was linked to clinical outcomes such as local control, residual disease, or survival, and emerging multi-marker protein signatures suggested that combinatorial approaches may outperform single-marker strategies. Radiosensitivity in cervical cancer is regulated by a network of biological pathways. Validated, integrated biomarker panels that capture DNA repair proficiency, stemness, hypoxia adaptation, and key signaling pathways are needed to improve risk stratification and enable biomarker-guided radiosensitization. Full article

Electrohydrodynamic emission from a sessile droplet depends on a coupled balance among electric traction, capillarity, gravity, charge transport and liquid motion. The present work addresses only the electrostatic-loading part of that problem. Verification-backed axisymmetric and three-dimensional Laplace solvers are used to map how parallel-plate, on-axis-pin, off-axis-pin and bipolar double-pin electrodes redistribute the normal electric field over a prescribed conducting water-droplet interface. The primary response is the dimensionless electric capillary number, Ca_E = ε₀E_n²R_v/γ. To compare geometries on a common voltage scale, V₁ is defined as the applied voltage at which the peak prescribed-interface loading reaches Ca_E = 1. V₁ is a normalisation voltage and not a jetting or stability threshold. The axisymmetric solver reproduces the exact conducting-hemisphere solution to within 0.07% at the finest grid. The three-dimensional finite-difference results are mesh-assessed, and their normalised surface-field topology is cross-checked against an independently implemented Galerkin finite-element model. At 4 kV, the finite parallel-plate cell produces an apex enhancement of 3.24 relative to V/H. Replacing the plate with an on-axis 1 mm pin reduces the apex field by 39.5%, which corresponds to a 63% reduction in Ca_E, and increases V₁ from approximately 5.0 to 8.2 kV. Lateral pin displacement moves the surface-field maximum away from the apex and produces a broad nominal plateau near d = 5–7 mm, although the sub-grid steering distance remains sensitive to mesh and extraction settings. The bipolar double-pin configuration produces two symmetric surface-field maxima together with a near-null at the apex. This topology, but not its absolute magnitude, is reproduced by the finite-element cross-check. A Gaussian-process model interpolates the one-dimensional offset family accurately under leave-one-offset-out validation (R² = 0.999). Four Bayesian-optimisation trials locate the broad steering plateau but show no visible evaluation-count advantage over random sampling in this one-dimensional test. A three-mesh study gives a reported field-magnitude mesh-sensitivity estimate of approximately 6.2% at the finest grid (rising to about 9.5% at the h = 0.20 mm production mesh) for the representative three-dimensional case, and an indicative combined-uncertainty band of approximately 10% is shown for V₁ in the exploratory trade-off plot. Illustrative Young–Laplace profiles at contact angles of 70° to 110° preserve the comparative pin-versus-plate field reduction, whereas V₁ varies by up to approximately 50%. A simplified Peek-law screening estimate places corona inception (the pin being cathodic) in the approximate range of 4.8–10 kV, which is comparable to the on-axis-pin V₁, so gas discharge may intervene before large electrocapillary loading is reached in ambient air. The results establish electrode geometry as a controllable electrostatic-loading parameter while explicitly deferring coupled stability analysis and experimental validation. By resolving this loading on a single exact-solution-verified basis, the study quantifies electrode geometry as a control parameter that idealised enhancement factors and the nominal gap field cannot capture and provides a verified fixed-interface reference state for subsequent coupled electrohydrodynamic modelling. Full article

Background/Objectives: Heart failure with reduced ejection fraction (HFrEF) involves coexisting inflammatory and hemostatic dysregulation contributing to thromboembolic and bleeding risk. Ten-eleven translocation (TET1-3) proteins regulate immune-cell phenotype, but their relationship to plasma coagulation parameters in HFrEF is poorly defined. We aimed to determine whether TET1-3 protein expression in peripheral blood leukocyte subpopulations is associated with routinely available plasma coagulation parameters in HFrEF, and whether associations differ by direct oral anticoagulant (DOAC) exposure and clinical phase. Methods: In this cross-sectional, observational, two-center study, 107 patients with HFrEF were enrolled (39 receiving a DOAC, non-randomized; 68 not receiving a DOAC, of whom seven received a vitamin K antagonist and 61 received no oral anticoagulant). TET1-3 protein expression was assessed by flow cytometry in T lymphocytes, B lymphocytes, natural killer (NK) cells, monocytes, and granulocytes, expressed as the ratio of test-to-negative-control geometric mean fluorescence intensity. Associations with activated partial thromboplastin time (aPTT) and international normalized ratio (INR) were analyzed using nonparametric tests and Spearman correlations; DOAC samples were drawn at steady-state trough. Results: DOAC-treated patients constituted a distinct clinical subgroup (older, predominantly AF/AFL) and showed longer aPTT and higher TET expression in selected immune-cell subsets; these between-group differences cannot be attributed to DOAC therapy. Patients with aPTT at or above the median showed higher TET expression in T cells, B cells, NK cells, and selected leukocyte indices, whereas INR-based stratification did not. In continuous analyses, TET indices showed multiple moderate positive Spearman correlations (R = 0.25–0.49) with both aPTT and INR—with INR showing the strongest single association—and no associations with composite inflammatory indices (NLR, SII, SIRI); all comparisons were exploratory and uncorrected for multiplicity. Associations appeared stronger in stable than in worsening HFrEF (exploratory). Conclusions: Peripheral leukocyte TET protein expression was associated with plasma coagulation parameters in HFrEF; the aPTT-specific pattern was confined to the categorical (median-split) analysis, whereas continuous analyses showed associations with both aPTT and INR. Because of the cross-sectional design, moderate sample size, and potential confounding by indication, these findings should be considered hypothesis-generating. TET-related immune-cell phenotyping may capture a non-redundant immune–coagulation signal in HFrEF and warrants prospective validation. Full article

Nutritional deterioration in adults with acute myeloid leukemia (AML) may be present at diagnosis and may evolve rapidly during intensive chemotherapy, lower-intensity treatment, and allogeneic hematopoietic cell transplantation (allo-HCT). This structured narrative review critically examines nutritional screening and diagnostic instruments, anthropometry and body composition, laboratory-derived composite indices, and objective physical-function measures. PubMed was searched for publications from 1 January 2015 through 13 July 2026; Google Scholar and reference lists were used foradditional citation searching. Of 292 records screened, 52 full-text reports were assessed and 34 empirical studies were included. Methodological limitations were appraised with the 2018 Mixed Methods Appraisal Tool. Evidence was heterogeneous and predominantly observational. PG-SGA and NRS-2002 identified nutritional risk and nutrition-impact symptoms, but their classifications were not interchangeable with GLIM diagnosis, body-composition phenotyping, or prognostic indices. BMI alone did not capture muscle depletion. CT, quantitative CT, BIA-derived phase angle, skeletal muscle indices, and repeated anthropometry detected clinically relevant changes, although thresholds varied and fluid shifts may bias BIA. Albumin-based indices, including CONUT, sCONUT, NRI, GNRI, PNI, and the C-reactive protein/albumin ratio, were associated with outcomes in several retrospective cohorts, but largely reflect inflammation, disease burden, and treatment effects as well as nutrition; no head-to-head evidence establishes superiority. SPPB, gait speed, walking tests, chair stands, and grip strength provided prognostic information in selected older and transplant cohorts, including patients treated with hypomethylating agents plus venetoclax. The evidence supports repeated, multimodal assessment, while remaining insufficient to prove that any single tool or tool-guided intervention improves survival. Future studies require standardized definitions, sex-stratified validation, contemporary treatment cohorts, and trials integrating nutrition, symptom control, and exercise. Full article

Background/Objectives: Non-invasive prenatal testing for monogenic disorders (NIPT-MD) provides a safe alternative to invasive procedures. However, its clinical utility is often limited by challenges such as low fetal fractions (FF), technical artifacts, and the difficulty in resolving maternally inherited pathogenic variants from the overwhelming background of maternal cell-free DNA (cfDNA). This study aimed to develop and validate a robust NIPT-MD platform for monogenic disorders, applicable across major common Mendelian inheritance patterns, by enhancing the accuracy of fetal variant detection in cfDNA. Methods: We developed a novel NIPT-MD platform validated using both simulated samples and a retrospective clinical cohort. The workflow involves a single-strand capture library preparation incorporating unique molecular identifiers (UMIs) to mitigate amplification artifacts. FF was precisely quantified using a fixed panel of high-minor-allele-frequency single-nucleotide polymorphisms (SNPs). Fetal genotypes were then inferred by resolving parental haplotypes through a statistical model that integrates weighting of variant allele frequency (VAF) and haplotype-informative SNP counts. Results: The single-strand capture protocol incorporating UMIs significantly reduced amplification biases. Validation of the fetal DNA fraction estimation algorithm revealed strong concordance with a Y-chromosome-derived method and expected spike-in samples. Optimization of the FF estimation panel conferred greater experimental stability. The platform reliably detected both paternally and maternally inherited pathogenic variants. In a retrospective cohort of 35 clinical cases, the NIPT-MD platform achieved high concordance with genotypes determined by invasive testing. Conclusions: These findings present an accurate and robust NIPT-MD platform for monogenic disorders, with high concordance to invasive testing validated in a retrospective cohort of 35 clinical cases. This method holds promise for clinical application in managing families at high risk of monogenic diseases. Full article